Big Data in Health Education: Exploring a Synergistic Collaboration in Machine Learning and Social Network Analysis
Recorded On: 07/22/2021
- Registration Closed
In the big data era, there is increasing interest in novel data sources that can inform health outcomes. In this webinar, we will discuss two popular methodologies (Natural Language Processing (NLP) and Social Network Analysis (SNA)) and how these methodologies can be synergistically combined to draw nuanced conclusions about health-related phenomena. Participants can expect demonstrations of NLP and SNA in practice, using timely examples relevant to a Public Health and Health Education audience. By the end of the webinar, participants will have learned strategies for incorporating big data into their own research/practice and tools for maximizing the validity of big data.
For more information on mining words, go to Dr. Valdez's co-authored article in Health Promotion and Practice https://journals.sagepub.com/d...
By the end of the 90-minute webinar, participants will be able to discuss various methods for analyzing big data and determine primary data collection needs, instruments, methods, and procedures to conduct big data studies in their own research. Sub Competency 1.2.7
Danny Valdez, PhD
Assistant Professor in the Department of Applied Health Science
Indiana University School of Public Health
Danny Valdez, PhD, is an Assistant Professor in the Department of Applied Health Science at the Indiana University School of Public Health, Bloomington. His research broadly focuses on language as data, leveraging social media and other big data sources to draw inferences about health phenomena. Part of his work is dedicated to Latinx sexual health behavior and procuring social media data from this population to understand sexual health needs and practices.
Megan S. Patterson, PhD, MPH
Assistant Professor in the Department of Health and Kinesiology
Texas A&M University
Megan S. Patterson, PhD, MPH, is an Assistant Professor in the Department of Health and Kinesiology at Texas A&M University. Her research focuses on using network analysis to measure how social and spatial networks impact the overall wellbeing of individuals and communities. Her training in research methods and network analysis provides ample opportunities to design, conduct, and collaborate on a variety of studies within behavioral science.
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